Psychological Health Outcomes Data

No discussion of data on health outcomes related to
the environment is complete without consideration of data on psychological
health outcomes. For purposes of this report, psychological health does
not include neurological disorders such as autism and learning disabilities,
i.e., those which have a largely physiological basis, and are considered
separately above. While neurological conditions are included in some the
information sources on psychological health, our focus here is upon data
outcomes with an emotional or perceptual basis linked to one’s
environment. This may include depression, stress, anxiety, and outcomes
and behaviors linked to one’s state of psychological well-being. However,
one should not discount that fact that psychological factors such as stress
are, in turn, linked to physiological conditions such as suppressed immune
response[352]and heart disease.[353]

Environmental factors can influence mental health
in numerous ways. For example, the features of a person’s perception of
their environment may affect their attitudes and behaviors. As discussed
later under the Built Environment section, several studies by Kuo et al.
illustrate that the presence of trees and green spaces can influence children’s
school performance, crime rates, and violent behavior.[354]Additionally,
environmental factors may stimulate behaviors beneficial to mental health
either directly or indirectly—for example, a nearby trail may encourage a
person to engage in physical activity, which may in turn lessen depression and
stress levels.

As with physical health, several different types of
outcome data for mental health exist. Although the aggregate levels at
which many of them are readily and publicly available are not geographically
detailed enough for serious environmental health research, we list a few of
them below. This will at least provide some starting points for obtaining
more detailed data if necessary.

These data sets may be very fragmented due to
different funding streams and administrative oversight for services. For
example, public agency datasets will exclude individuals whose treatment is not
partially or entirely covered by public funds, e.g., those pay out-of-pocket
for private treatment. Laws originally set up to protect individual
privacy can make it difficult for bureaus overseeing different types of
services to the same individual to share information with one another.[355]
Also, many individuals from low-income backgrounds have poorer access to care,
either due to lack of health insurance or other coverage, difficulty obtaining
transportation access to health care providers, a lack of time to spend waiting
in exceptionally crowded facilities (e.g., hospital waiting rooms in
underserved areas), schedule constraints due to job and family (e.g., a single
mother working two jobs that offer little or no sick/vacation leave), or lack
of education regarding the importance of preventive treatment. Thus,
their mental health conditions may never even show up in service utilization data.

The Pennsylvania Health Care Cost Containment
Council (PHC4) dataset described above contains information on individuals
involuntarily admitted for emergency treatment “necessary to
protect the life or health, or both, of the individual or to control behavior
by the individual which is likely to result in physical injury to others.” [356], [357]
The Allegheny County Department of Human Services (DHS) maintains various
datasets internally, but privacy and confidentially concerns must be addressed
before such data can be shared more openly. Additionally, limited
treatment data, aggregated for large areas, are available online. Within
the U.S. Department of Health and Human Services, the Substance Abuse and
Mental Health Services Administration’s (SAMHSA) Office of Applied Studies
website provides data including state and county-level statistics on substance
abuse treatment admissions, and metropolitan area statistics for drug-related
emergency room visits and drug-related deaths.[358]

A child’s environment may impact such psychological
health factors as their ability to pay attention in school and self-discipline,
which in turn may be reflected in their performance on standardized educational
tests[359]
and behaviors such as school attendance rate. School-district level data
for the entire state is available through Standard and Poor’s School Evaluation
website.[360]
These include data on standardized test passing rates, attendance rates,
dropout rates and disciplinary sanctions, along with various other school
district characteristics (e.g., spending per student and percent economically
disadvantaged) that also impact these data—and must thus be controlled for in
any statistical study. Some of these data are also available through the
Pennsylvania Department of Education’s website,[361] and accompanying school-level
demographics can be obtained through the Pittsburgh Public School Data Atlas at
the University of Pittsburgh’s VisualInformationSystemsCenter.[362]

Section 618 of the Individuals with Disabilities
Education Act (IDEA) requires school districts to annually report data on
enrollment numbers for children receiving special education services to the
U.S. Department of Education. These include data on children ages birth
through 2, and 3 though 21+.[363]
Although it includes primarily neurological disorders, which are addressed
above, it also includes some psychological conditions. The Pennsylvania
Department of Education’s “Penn Data Special Education Reporting System”
reports include numbers of enrolled children with conditions including mental
retardation, hearing impairments, speech or language impairments, visual
impairments, emotional disturbance, orthopedic impairments, specific learning
disabilities, deaf-blindness, multiple disabilities, autism, and developmental
delay.[364]
These reports include data summarized for each of Pennsylvania’s 29 intermediate unit regions,
as well as school districts within each region and charter schools, for school
years 1990-1991 through 2003-2003. The U.S. Department of Education’s
IDEAdata.org website also has state-level reports with much of this
information.[365]

As discussed later under the Built Environment
section, one’s environment may elicit psychological and behavioral
responses—i.e., lack of exposure to green space may be linked to violence and
criminal behavior.[366],[367] In addition to the
Pittsburgh Police Department reports data listed in the Built Environment
section, some data are more easily accessible but on a larger geographic
scale. The FBI Uniform Crime Reports (UCR) include arrests and reported offenses
collected and reported by local police departments. Data are broken out
by different categories of crime, including violent versus non-violent
offenses. One should keep in mind that these do not reflect data such as
911 calls where police were dispatched, but no report was filed. Some
crime information at a sub-city level, including data on serious assaults and
homicides for Pittsburgh, is available at the
website of the National Consortium on Violence Research (NCOVR),[368]
headquarted locally at CarnegieMellonUniversity’s
Heinz School of Public Policy and Management. As for school violence, the
State Department of Education’s School Violence and Weapons Possession
Reporting System includes county-level data for the 1999-2000 through 2002-2003
school years.[369]
Data on reported and investigated child abuse and neglect, another type
of violent behavior, is maintained by the Pennsylvania Department of Welfare,
Office of Children, Youth and Families.[370] Death records, mentioned earlier
in the Health Outcomes Section, include causes of death such as homicide.[371]
For most types of crime and violent behavior data, however, keep in mind that a
great deal may never even be reported.

This may include self-reported perception of
psychological well-being, behaviors associated with psychological well-being,
and utilization of mental health services (e.g., “How often do you visit a
counselor for depression?”). Due to the cost and effort of gathering such
data, they are generally for a small proportion of people over a large
geographic area, or a somewhat larger proportion of people within a very
limited geographic area. The Behavioral Risk Factor Surveillance System
(BRFSS) mentioned earlier, which included an expanded example for Pittsburgh,[372]
includes data on self-reported alcohol use. The National Institute of
Mental Health’s Epidemiologic Catchment Area (ECA) Program surveyed more than
20,000 respondents across five cities in the early 1980s. Its goals
included gathering data on the prevalence and incidence of 17 major mental
disorders.[373],[374] In the early 1990s, the National
Comorbidity Survey (NCS) sought to gather data on mental health disorders using
a nationally representative sample. These respondents were interviewed
again in 2001-2002 for the NCS-2, and 10,000 new respondents were added through
the NCS Replication Survey (NCS-R).[375],[376]
These studies may serve as models for gathering more comprehensive data in the Pittsburgh region, with
sample sizes large enough for analysis alongside small-area environmental
factors.

Psychological health data have a few general
limitations. One is that a particular psychological illness or condition
may or may not be reflective of an individual’s more global mental health or
state of psychological well-being, or their perceived quality of life.[377]
Frequently, we have only a small piece of the overall picture.
Additionally, a person’s current condition may have been shaped by previous
experiences in a completely different environment. A child attending
school in one district may have been born and raised in a community with a
completely different mix of environmental factors. Furthermore, whereas
many physiological conditions can be represented by data on a simple binary
basis (e.g., either a person has had cancer or they have not), many
psychological conditions may be better represented on a continuous scale (e.g.,
sometimes sad, always sad) that may not be accurately represented in a data
set. Having a diagnosed condition such as clinical depression from the
DSM, or Diagnostic and Statistical Manual of Mental Disorders, would be
the closest approximation of such binary data. Even so, mental disorders
are difficult to quantify because their diagnosis often involves a certain
symptom “threshold,” i.e., the individual must exhibit a certain number of
symptoms over a certain period of time.[378] Also, diagnoses as defined in the
Diagnostic and Statistical Manual of Mental Disorders (DSM) change with
each revision.

Finally, little data exist on some pertinent
topics. For example, some evidence suggests that feelings of personal
inadequacy are linked to materialistic behavior.[379] This might include, for example,
purchasing a larger house and larger automobile in an attempt to compensate for
feelings of inadequacy. Such materialistic behavior, in turn, may further
deteriorate the environment and impact health, as described in the Consumer
Demands and Polluting Activities section and elsewhere.[380] While there do not currently
appear to be any comprehensive data sources on insecurity and feelings of
self-worth, surveys collecting such data could be informative to the
environmental health community.